Dice Wars

Dice Wars is a strategy game where players take turns to attack adjacent territories to expand their area. Each territory contains a number of dice determining player's presence and strength. The objective of the game is to conquer all territories and thus eliminate each opponent.

This is a client-server implementation that was created as a part of my bachelor's thesis where it is described in more detail.

Usage

To use this, you need to have python3 and the following python packages:

hexutil
numpy
pyqt

To play the game, use the dicewars.py script with the following options:

-n    number of players, could be 2-8 with 2 being the default value
-p    port, default 5005
-a    address, default is localhost
--ai  list of ai versions to play against (possible values 1-4, default 1)

Example:

./dicewars.py -n 4 --ai 4 2 1  # run a 4-player game against ai versions 4, 2 and 1

List of AI players

Naive (AI 1)

This agent performs all possible moves in random order

Strength Difference Checking (AI 2)

This agent prefers moves with highest strength difference and doesn't make moves against areas with higher strength.

Single Turn Expectiminimax (AI 3)

This agent makes such moves that have a probability of successful attack and hold over the area until next turn higher than 20 %.

Improved Single Turn Expectiminimax (AI 4)

This agent makes such moves that have a probability of successful attack and hold over the area until next turn higher a 20% in two-player games and higher than 40% in four-player games. In addition, it prefers attacks initiated from its largest region.

Win Probability Maximization using Scores (AI 5)

This agent estimates win probability given the current state of the game. As a feature to describe the state, a vector of players' scores is used. The agent choses such moves, that will have the highest improvement in the estimated probability.

Win Probability Maximization using Dice (AI 6)

This agent estimates win probability given the current state of the game. As a feature to describe the state, a vector of logarithms of players' scores is used. The agent choses such moves, that will have the highest improvement in the estimated probability.

Win Probability Maximization using Scores and Dice (AI 7)

This agent estimates win probability given the current state of the game. As a feature to describe the state, a vector of logarithms of players' dice and scores is used. The agent choses such moves, that will have the highest improvement in the estimated probability.